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Robert E Wiltbank, Ph.D.
wiltbank@willamette.edu
-
10
20
30
40
50
60
<1X 1X to 5X 5X to 10X 10X to 30X >30X
Exit Multiple
PercentofExits
Distribution of Returns by Venture Investment
Red Bars: U.K. % of exits in that Category
Blue bars: U.S. % of exits in that Category
UK: Overall Multiple: 2.2X
Holding Period: 3.6 years
US: Overall Multiple: 2.6X
Holding Period: 3.5 years
Approx 22% IRR
Approx 27% IRR
Hold: 3.0 yrs.
Hold: 3.3 yrs.
Hold: 4.6 yrs.
Hold: 4.9 yrs. Hold: 6.0+ yrs.
0
10
20
30
40
50
60
< 1X 1X to 5X 5X to 10X 10X to 30X > 30X
Exit Multiples
PercentofTotalExits
Distribution of Returns by Venture Investment
Overall Multiple: 2.6X
Avg. Holding Period: 3.5 years
$20M
$40M
$60M
$80M
Blue bars: % of exits in that Category
Green Bars: $’s returned in that Category
Hold: 3.0 yrs.
Hold: 3.3 yrs.
Hold: 4.6 yrs.
Hold: 4.9 yrs. Hold: 6.0 yrs.
Outcomes Split by Industry Expertise
-
10.0
20.0
30.0
40.0
50.0
60.0
70.0
<1X 1X to 5X 5X to 10X 10X to 30X >30X
Multiple Category
PercentofExits
No Industry Expertise Some Industry Expertise
60% better multiple for deals
related to industry expertise
Outcomes Split by Due Diligence
-
10.0
20.0
30.0
40.0
50.0
60.0
70.0
<1X 1X to 5X 5X to 10X 10X to 30X >30X
Multiple Category
PercentofExits
Less Than 20 Hours 20+ Hours
2X better multiple
for 20+ due diligence
-
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
< 1X 1X to 5X 5X to 10X 10X to 30X > 30X
Exit Multiples
PercentofExits
Follow On Yes Follow On No
Follow-On Investment from Same Angel Investor
No 3.6X (3.3 years)
Yes 1.4X (3.9 years)
30% of deals had follow on
investments.
-
10.0
20.0
30.0
40.0
50.0
60.0
70.0
< 1X 1X to 5X 5X to 10X 10X to 30X > 30X
Exit Multiples
PercentofExits
VC No VC
Venture Capital Involvement
35% of deals took on VC
investment at some point
• Smaller venture deals do get to exits
• The returns to those deals are quite attractive
ROI equates if 3 and 7 year holding periods
Returns to Invested Capital
ROI equates if smaller deals fail 91% of the time
AcquisitionsofPrivateVenturesbyPublicCorporations
PaidInCapitalRange DealCount
Median
Price
MedianPaid
inCapital
Median
Multiple
Sumof
Price
SumPaidIn
Capital
Aggregate
Multiple
Aggregate
Profit
Profit$'s
perdeal
Hypothetical
ROI
$5M-$100M 322 60.2 14.0 3.5 34,914 8,260 4.2 26,654 82.8 20% 30%failurerate
under$5M 1,359 10.3 0.2 53.6 35,741 931 38.4 34,810 25.6 48% 70%failurerate
WholeSample 1,530 14.8 0.5 24.5 70,655 9,192 7.7 61,463 40.2 29%
IncludesONLYdealswithaMULTIPLEOFATLEAST1
IncludesONLYdealswithcompletedata(70%oftransactions)
Robert E Wiltbank, Ph.D
• Transaction Economics vs. Macro Economics
Price Cost T.A.M.
Contribution Margin Predicted Market shares
Historical Data
Cost of Customer Acq Comparables
Customer ROI
Key Target List
• Cash to Cash cycles & Capital Intensity
Longest lead time supply Production cycle
Sales Cycle Order/Shipment gap
Days in AP
Details in Due Diligence
– Select ventures that appear most capable of influencing critical market elements.
Create and influence localized markets OR
Compete in large growing markets
– Emphasize the current means and capabilities of the venture rather than on plans for
acquiring the “best” means to reach their original goals.
Adjust goals to use current means OR
Acquire means critical to insightful goals
– Encourage the venture to make smaller investments that get to cash flow positive
rather than investing in the resources suggested by market research to “hit plan.”
Overhead trails growth OR
Pre-position assets to time great opportunity
– Avoid prediction as the basis for investment decisions.
Emphasize affordable loss OR
Maximize expected values
Early stage investing perspectives
Investors prefer opportunities:
in large and fast growing markets
with customers lined up waiting to repeatedly buy a high margin product
where no powerful competitors exist
with the potential to ‘keep others out’ of the market
led by experts in the field who have prior entrepreneurial success
The problem is the sequence; prioritization
i.e. insightful market research to demonstrate market potential,
or win a great beta customer?
i.e. win a new great team member
or finish the prototype to demonstrate claims?
Selecting ventures for investment
Staged Decisions in Angel Investing
• Angels use predictive information more than they think
– Especially early in the process
• This shifts as we approach actual investment decisions
• Investors with more Entre Experience Prefer Non-Predictive Info.
-2.16 0.00 -3.41 0.00 0.10 0.50 -4.07 0.00
0.52 0.00 0.42 0.00 0.09 0.00 0.05 0.05
0.17 0.00 0.21 0.00 0.16 0.00 0.17 0.00
S and multinomial or binary logistic regression.
N = 2156
Adj R2 = .040Adj R2 = .455
N = 2383
Adj R2 = .409
N = 2109
Adj R2 = .046
N = 2283
DD1 DD3 DDP2 FundedDependent Variable
Constant
Inv Entre
Inv Angel
Eval Prediction
Eval Control
Prediction Emphasis
Control Emphasis
Cognitive Matching between VC’s and Entre’s
Conjoint analysis of VC investment evaluation.
Simultaneous manipulation of preferences
1. The match between VC’s and Entre’s significantly increased funding
2. Social Capital and Match were jointly as ‘powerful’ as the economics
Economics: Hi Potential vs. Moderate
Social Capital: Strong rep and Referrals vs. Moderate
Entre Mindset: Effectual vs. Causal
VERY Active Angels
• Interviewed 30 “Super” Angels
• Average of about 30 angel investments.
• Min $8M invested (max of $100M)
• Amgen, Autocad, Google, Intel, Apple, Twitter,
National Semiconductor, Sun Micro, Plaxo,
Guidant, Silicon Valley Bank, Teledyne
Searching For Something
• What role does their network play in their investing?
• What is their approach to angel investing?
Criteria, Strategy, Process, “Rules” etc.
• How do they manage investments after the fact?
• What have they learned along the way?
3 key findings to date
• From experience: Better at reading people
– No quitters, no liars, no jerks, big passion
– real FIT between the person and the opportunity.
– Some love “coachability” but not all.
• Major Sector Focus
– Med Devices is not Bio Tech
– Consumer Internet is not Network Technology
– Software is not hardware.
– Software isn’t even software
• Strategies: Equifinality
Equifinality: Many paths same end
• Broad and Thin, support in “key moments,” team
interaction is critical, no follow unless “no-brainer”
• Co-Founder: start with 100% ownership, use it to build
team and opportunity
• Wealthy Sector Expert: go deep on funding as needed,
forget co-investors, work with experts you know
Strategic Coherence, Yes (though not always consistent)
Robert E Wiltbank, Ph.D.
wiltbank@willamette.edu
Effectual vs. Predictive Logic
Given
Goals
M1
M2
M3
M4
M5
Distinguishing Characteristic Of Predictive Logic:
Selecting various means to achieve pre-determined goals
New means may be generated over time
Distinguishing Characteristic of Effectuation:
Imagining & Selecting various goals using a given set of means
E2
E3
E
En
Given Means
M1
M2
M3
M4
M5
E1
Imagined
Ends
Effectual vs. Predictive Logic
What CAN we do, rather than what SHOULD we do.
21
Definition of one of several possible markets
Adding Segments/Strategic Partners
Segment Definition
(through strategic partnerships & “selling”)
Market Definition
Segmentation
(using relevant variables such as age, income, etc.)
Effectuation
Causation Model
from Expert managers
Targeting
(based on evaluation criteria
such as expected return)
Positioning
(through mktg strategies)
Effectuation as Used
by Expert Entrepreneurs
Customer
Identification
(through Who am I?
What do I know?
Whom do I know?)
THE CUSTOMER
Prediction vs. Control
Prediction: To the extent that I can predict the future, I can control my outcomes.
efforts to insightfully position for success based on expectations/forecasts for the
development of important market elements. This often includes modeling event spaces, estimating
probabilities and consequences, and forming sophisticated portfolio strategies with multiple options.
Assumes that market elements are predominantly independent of the organization.
Control: To the extent that I can control the future, I do not need to predict it.
efforts to deliberately construct/create market elements, such as defined products, articulated
demand preferences, and market structures (i.e. channels, technical standards, common practices).
Assumes either the non-existence of some key elements, or the organization’s ability to significantly
affect the evolution of those elements.
Prediction is uniquely difficult with new ventures,
while efforts to directly construct markets may be particularly effective.
Predictive. The future is a reliable
continuation of the past. Accurate
prediction is possible and useful.
Transformative. The future as shaped (at least
partially) by actions of all players. Prediction is
neither easy nor useful.
5. Approach
Avoid Contingencies. Surprises are
bad. Contingencies are managed by
careful planning and focus on
targets.
Leverage Contingencies. Surprises are good.
New developments encourage imaginative re-
thinking of possibilities and continual
transformations of targets.
4. Contingency
Perform Competitive Analysis. Protect.
Strategy is driven by potential
competitive threats.
Form Partnerships. Grow. Strategy is created
jointly through partnerships to create new
opportunities.
3. Attitude
Toward
Outsiders
Calculate Expected Return. Pursue the
(risk adjusted) largest opportunity
and accumulate required resources.
Maximize upside potential.
Set Affordable Loss. Pursue interesting
opportunities without investing more
resources than you can afford to lose. Set a
limit on downside potential.
2. Risk, Return
and
Resources
Set a Goal. Goals determine actions. For
example, the goal of achieving X, will
dictate I need person A with skills
matched to X.
Assess Your Means. Take action based on what
you have available:
* Who I am
* What I know
* Whom I know
Example: I have person A, I can achieve X, Y, or Z
1. Where to
Start
Tactics for PredictionTactics for Control
Predictive. The future is a reliable
continuation of the past. Accurate
prediction is possible and useful.
Transformative. The future as shaped (at least
partially) by actions of all players. Prediction is
neither easy nor useful.
5. Approach
Avoid Contingencies. Surprises are
bad. Contingencies are managed by
careful planning and focus on
targets.
Leverage Contingencies. Surprises are good.
New developments encourage imaginative re-
thinking of possibilities and continual
transformations of targets.
4. Contingency
Perform Competitive Analysis. Protect.
Strategy is driven by potential
competitive threats.
Form Partnerships. Grow. Strategy is created
jointly through partnerships to create new
opportunities.
3. Attitude
Toward
Outsiders
Calculate Expected Return. Pursue the
(risk adjusted) largest opportunity
and accumulate required resources.
Maximize upside potential.
Set Affordable Loss. Pursue interesting
opportunities without investing more
resources than you can afford to lose. Set a
limit on downside potential.
2. Risk, Return
and
Resources
Set a Goal. Goals determine actions. For
example, the goal of achieving X, will
dictate I need person A with skills
matched to X.
Assess Your Means. Take action based on what
you have available:
* Who I am
* What I know
* Whom I know
Example: I have person A, I can achieve X, Y, or Z
1. Where to
Start
Tactics for PredictionTactics for Control
Non-Predictive Control: Effectuation

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FiBAN's business angel training "Business Angel Returns" by Robert Wiltbank - Presentation "Promising outcomes and effective strategies"

  • 1. Robert E Wiltbank, Ph.D. wiltbank@willamette.edu
  • 2. - 10 20 30 40 50 60 <1X 1X to 5X 5X to 10X 10X to 30X >30X Exit Multiple PercentofExits Distribution of Returns by Venture Investment Red Bars: U.K. % of exits in that Category Blue bars: U.S. % of exits in that Category UK: Overall Multiple: 2.2X Holding Period: 3.6 years US: Overall Multiple: 2.6X Holding Period: 3.5 years Approx 22% IRR Approx 27% IRR Hold: 3.0 yrs. Hold: 3.3 yrs. Hold: 4.6 yrs. Hold: 4.9 yrs. Hold: 6.0+ yrs.
  • 3. 0 10 20 30 40 50 60 < 1X 1X to 5X 5X to 10X 10X to 30X > 30X Exit Multiples PercentofTotalExits Distribution of Returns by Venture Investment Overall Multiple: 2.6X Avg. Holding Period: 3.5 years $20M $40M $60M $80M Blue bars: % of exits in that Category Green Bars: $’s returned in that Category Hold: 3.0 yrs. Hold: 3.3 yrs. Hold: 4.6 yrs. Hold: 4.9 yrs. Hold: 6.0 yrs.
  • 4. Outcomes Split by Industry Expertise - 10.0 20.0 30.0 40.0 50.0 60.0 70.0 <1X 1X to 5X 5X to 10X 10X to 30X >30X Multiple Category PercentofExits No Industry Expertise Some Industry Expertise 60% better multiple for deals related to industry expertise
  • 5. Outcomes Split by Due Diligence - 10.0 20.0 30.0 40.0 50.0 60.0 70.0 <1X 1X to 5X 5X to 10X 10X to 30X >30X Multiple Category PercentofExits Less Than 20 Hours 20+ Hours 2X better multiple for 20+ due diligence
  • 6. - 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 < 1X 1X to 5X 5X to 10X 10X to 30X > 30X Exit Multiples PercentofExits Follow On Yes Follow On No Follow-On Investment from Same Angel Investor No 3.6X (3.3 years) Yes 1.4X (3.9 years) 30% of deals had follow on investments.
  • 7. - 10.0 20.0 30.0 40.0 50.0 60.0 70.0 < 1X 1X to 5X 5X to 10X 10X to 30X > 30X Exit Multiples PercentofExits VC No VC Venture Capital Involvement 35% of deals took on VC investment at some point
  • 8. • Smaller venture deals do get to exits • The returns to those deals are quite attractive ROI equates if 3 and 7 year holding periods Returns to Invested Capital ROI equates if smaller deals fail 91% of the time AcquisitionsofPrivateVenturesbyPublicCorporations PaidInCapitalRange DealCount Median Price MedianPaid inCapital Median Multiple Sumof Price SumPaidIn Capital Aggregate Multiple Aggregate Profit Profit$'s perdeal Hypothetical ROI $5M-$100M 322 60.2 14.0 3.5 34,914 8,260 4.2 26,654 82.8 20% 30%failurerate under$5M 1,359 10.3 0.2 53.6 35,741 931 38.4 34,810 25.6 48% 70%failurerate WholeSample 1,530 14.8 0.5 24.5 70,655 9,192 7.7 61,463 40.2 29% IncludesONLYdealswithaMULTIPLEOFATLEAST1 IncludesONLYdealswithcompletedata(70%oftransactions) Robert E Wiltbank, Ph.D
  • 9. • Transaction Economics vs. Macro Economics Price Cost T.A.M. Contribution Margin Predicted Market shares Historical Data Cost of Customer Acq Comparables Customer ROI Key Target List • Cash to Cash cycles & Capital Intensity Longest lead time supply Production cycle Sales Cycle Order/Shipment gap Days in AP Details in Due Diligence
  • 10. – Select ventures that appear most capable of influencing critical market elements. Create and influence localized markets OR Compete in large growing markets – Emphasize the current means and capabilities of the venture rather than on plans for acquiring the “best” means to reach their original goals. Adjust goals to use current means OR Acquire means critical to insightful goals – Encourage the venture to make smaller investments that get to cash flow positive rather than investing in the resources suggested by market research to “hit plan.” Overhead trails growth OR Pre-position assets to time great opportunity – Avoid prediction as the basis for investment decisions. Emphasize affordable loss OR Maximize expected values Early stage investing perspectives
  • 11. Investors prefer opportunities: in large and fast growing markets with customers lined up waiting to repeatedly buy a high margin product where no powerful competitors exist with the potential to ‘keep others out’ of the market led by experts in the field who have prior entrepreneurial success The problem is the sequence; prioritization i.e. insightful market research to demonstrate market potential, or win a great beta customer? i.e. win a new great team member or finish the prototype to demonstrate claims? Selecting ventures for investment
  • 12. Staged Decisions in Angel Investing • Angels use predictive information more than they think – Especially early in the process • This shifts as we approach actual investment decisions • Investors with more Entre Experience Prefer Non-Predictive Info. -2.16 0.00 -3.41 0.00 0.10 0.50 -4.07 0.00 0.52 0.00 0.42 0.00 0.09 0.00 0.05 0.05 0.17 0.00 0.21 0.00 0.16 0.00 0.17 0.00 S and multinomial or binary logistic regression. N = 2156 Adj R2 = .040Adj R2 = .455 N = 2383 Adj R2 = .409 N = 2109 Adj R2 = .046 N = 2283 DD1 DD3 DDP2 FundedDependent Variable Constant Inv Entre Inv Angel Eval Prediction Eval Control Prediction Emphasis Control Emphasis
  • 13. Cognitive Matching between VC’s and Entre’s Conjoint analysis of VC investment evaluation. Simultaneous manipulation of preferences 1. The match between VC’s and Entre’s significantly increased funding 2. Social Capital and Match were jointly as ‘powerful’ as the economics Economics: Hi Potential vs. Moderate Social Capital: Strong rep and Referrals vs. Moderate Entre Mindset: Effectual vs. Causal
  • 14. VERY Active Angels • Interviewed 30 “Super” Angels • Average of about 30 angel investments. • Min $8M invested (max of $100M) • Amgen, Autocad, Google, Intel, Apple, Twitter, National Semiconductor, Sun Micro, Plaxo, Guidant, Silicon Valley Bank, Teledyne
  • 15. Searching For Something • What role does their network play in their investing? • What is their approach to angel investing? Criteria, Strategy, Process, “Rules” etc. • How do they manage investments after the fact? • What have they learned along the way?
  • 16. 3 key findings to date • From experience: Better at reading people – No quitters, no liars, no jerks, big passion – real FIT between the person and the opportunity. – Some love “coachability” but not all. • Major Sector Focus – Med Devices is not Bio Tech – Consumer Internet is not Network Technology – Software is not hardware. – Software isn’t even software • Strategies: Equifinality
  • 17. Equifinality: Many paths same end • Broad and Thin, support in “key moments,” team interaction is critical, no follow unless “no-brainer” • Co-Founder: start with 100% ownership, use it to build team and opportunity • Wealthy Sector Expert: go deep on funding as needed, forget co-investors, work with experts you know Strategic Coherence, Yes (though not always consistent)
  • 18. Robert E Wiltbank, Ph.D. wiltbank@willamette.edu
  • 19. Effectual vs. Predictive Logic Given Goals M1 M2 M3 M4 M5 Distinguishing Characteristic Of Predictive Logic: Selecting various means to achieve pre-determined goals New means may be generated over time
  • 20. Distinguishing Characteristic of Effectuation: Imagining & Selecting various goals using a given set of means E2 E3 E En Given Means M1 M2 M3 M4 M5 E1 Imagined Ends Effectual vs. Predictive Logic What CAN we do, rather than what SHOULD we do.
  • 21. 21 Definition of one of several possible markets Adding Segments/Strategic Partners Segment Definition (through strategic partnerships & “selling”) Market Definition Segmentation (using relevant variables such as age, income, etc.) Effectuation Causation Model from Expert managers Targeting (based on evaluation criteria such as expected return) Positioning (through mktg strategies) Effectuation as Used by Expert Entrepreneurs Customer Identification (through Who am I? What do I know? Whom do I know?) THE CUSTOMER
  • 22. Prediction vs. Control Prediction: To the extent that I can predict the future, I can control my outcomes. efforts to insightfully position for success based on expectations/forecasts for the development of important market elements. This often includes modeling event spaces, estimating probabilities and consequences, and forming sophisticated portfolio strategies with multiple options. Assumes that market elements are predominantly independent of the organization. Control: To the extent that I can control the future, I do not need to predict it. efforts to deliberately construct/create market elements, such as defined products, articulated demand preferences, and market structures (i.e. channels, technical standards, common practices). Assumes either the non-existence of some key elements, or the organization’s ability to significantly affect the evolution of those elements. Prediction is uniquely difficult with new ventures, while efforts to directly construct markets may be particularly effective.
  • 23. Predictive. The future is a reliable continuation of the past. Accurate prediction is possible and useful. Transformative. The future as shaped (at least partially) by actions of all players. Prediction is neither easy nor useful. 5. Approach Avoid Contingencies. Surprises are bad. Contingencies are managed by careful planning and focus on targets. Leverage Contingencies. Surprises are good. New developments encourage imaginative re- thinking of possibilities and continual transformations of targets. 4. Contingency Perform Competitive Analysis. Protect. Strategy is driven by potential competitive threats. Form Partnerships. Grow. Strategy is created jointly through partnerships to create new opportunities. 3. Attitude Toward Outsiders Calculate Expected Return. Pursue the (risk adjusted) largest opportunity and accumulate required resources. Maximize upside potential. Set Affordable Loss. Pursue interesting opportunities without investing more resources than you can afford to lose. Set a limit on downside potential. 2. Risk, Return and Resources Set a Goal. Goals determine actions. For example, the goal of achieving X, will dictate I need person A with skills matched to X. Assess Your Means. Take action based on what you have available: * Who I am * What I know * Whom I know Example: I have person A, I can achieve X, Y, or Z 1. Where to Start Tactics for PredictionTactics for Control Predictive. The future is a reliable continuation of the past. Accurate prediction is possible and useful. Transformative. The future as shaped (at least partially) by actions of all players. Prediction is neither easy nor useful. 5. Approach Avoid Contingencies. Surprises are bad. Contingencies are managed by careful planning and focus on targets. Leverage Contingencies. Surprises are good. New developments encourage imaginative re- thinking of possibilities and continual transformations of targets. 4. Contingency Perform Competitive Analysis. Protect. Strategy is driven by potential competitive threats. Form Partnerships. Grow. Strategy is created jointly through partnerships to create new opportunities. 3. Attitude Toward Outsiders Calculate Expected Return. Pursue the (risk adjusted) largest opportunity and accumulate required resources. Maximize upside potential. Set Affordable Loss. Pursue interesting opportunities without investing more resources than you can afford to lose. Set a limit on downside potential. 2. Risk, Return and Resources Set a Goal. Goals determine actions. For example, the goal of achieving X, will dictate I need person A with skills matched to X. Assess Your Means. Take action based on what you have available: * Who I am * What I know * Whom I know Example: I have person A, I can achieve X, Y, or Z 1. Where to Start Tactics for PredictionTactics for Control Non-Predictive Control: Effectuation